University of Duisburg-Essen
University of Duisburg-Essen
Ruhr Graduate School
2025-05-16
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EfeMOD Project
Motivation and Objective
Data
Empirical Approach
Results
Conclusion / Outlook
Empirisch fundierte Elektrizitätsmarkt-Modellierung mit Open Data
Project Entities:
Chair of Prof. Dr. Christoph Weber (Management Sciences and Energy Economics)
Chair of Prof. Dr. Florian Ziel (Data Science in Energy and Environment)
Project Goal:
Use publicly available data (particularly ENTSO-E Transparency Platform) to estimate parameters for energy system and energy market models.

Hallo World!
Identification of Power Plant Operation States Using Clustering
Gain Knowledge about the Power Plant Characteristics
This Presentation:
Identify Operation States:
Provide these characteristics to other researchers
e.g. to estimate efficiency
Model-Based Clustering of the Regions using mclust::Mclust in R.
Obtain finite mixture distribution:
\[\sum_{k=1}^{G}{\pi_k f_k (\mathbf{x}; \mathbf{\theta}_k)}\]
\(f_k\) Density of k’s component
\(\pi_k\) Mixture weights
\(\theta_k\) parameters of k’s density component
\[ x =\sum_{i = 1}^{6} x_i \tag{1} \label{eq:einste} \]
\[ E = mc^2 \tag{2} \label{eq:eiein} \]
And here we reference equation (\(\ref{eq:einste}\)) again.
According to recent studies, electricity markets are changing rapidly (Smith, 2020).
RuhrMetrics Seminar